Senior Software Engineer - 3D Modeling

At Hover, we empower individuals to design, enhance, and safeguard their cherished properties. Utilizing proprietary AI technology built on over a decade of real property data, we provide answers to pressing questions such as “What will it look like?” and “What will it cost?” Homeowners, contractors, and insurance professionals depend on Hover to receive fully measured, accurate, and interactive 3D models of any property—achieved through a smartphone scan in mere minutes.We are driven by curiosity, purpose, and a collective commitment to our customers, communities, and each other. At Hover, we believe the most innovative ideas stem from diverse perspectives, and we take pride in fostering an inclusive, high-performance culture that encourages growth, accountability, and excellence. Supported by leading investors like Google Ventures and Menlo Ventures, and trusted by industry leaders including Travelers, State Farm, and Nationwide, we are transforming how people perceive and interact with their environments.Why Join Hover?At Hover, 3D models are not just a feature; they are the essence of our product. Each scan and data point we process empowers homeowners, insurers, and contractors to make informed, data-driven decisions. We are seeking a Software Engineer who has a passion for geometry, automation, and making a tangible impact in the real world. In this role, you will design and implement systems that convert customer-captured imagery into meticulously accurate 3D models, enhancing the scalability and precision of Hover’s modeling pipeline. You will work collaboratively with designers and engineers across frontend, backend, computer vision, and DevOps to bring innovative capabilities to fruition, blending technical expertise with strong communication and cross-functional collaboration.The 3D Modeling Pipeline team develops the tools essential for our in-house operations to transform customer-captured scans into highly detailed, accurate 3D models of buildings. This team is also responsible for creating the pipeline and systems that process 3D data through both automated and manual steps, as well as exporting data into customer-facing formats.Your Contributions Will Include:Owning and evolving backend systems that convert raw scan data into exact 3D models, ensuring timely delivery to key ecosystem partners like Xactimate and Cotality.Building and refining internal modeling tools that enable teams to efficiently generate, validate, and optimize high-quality 3D data.Collaborating with machine learning and computer vision engineers to implement new algorithms into production, bridging research with practical applications.Enhancing customer and partner experiences by improving how Hover’s 3D outputs integrate with downstream workflows and external platforms.Promoting innovation and ongoing enhancement across our modeling pipeline.

At Hover, we empower individuals to design, enhance, and safeguard the properties they cherish. Utilizing our proprietary AI, developed over a decade of extensive real property data, we adeptly address crucial inquiries such as “What will it look like?” and “What will it cost?” Homeowners, contractors, and insurance professionals depend on Hover for fully measured, precise, and interactive 3D models of any property, all achievable through a smartphone scan in mere minutes.Driven by curiosity, purpose, and a shared dedication to our customers, communities, and one another, we believe that the most innovative ideas stem from diverse viewpoints. We are proud to foster an inclusive, high-performance culture that encourages growth, accountability, and excellence. Supported by prominent investors like Google Ventures and Menlo Ventures, and trusted by industry leaders such as Travelers, State Farm, and Nationwide, we are revolutionizing how people perceive and engage with their spaces.Why Hover is Seeking YouIn our team, 3D models are not just a feature; they are fundamental to our offering. Each scan and data point we process empowers homeowners, insurers, and contractors to make informed, data-driven decisions. We are on the lookout for a Software Engineer who is enthusiastic about geometry, automation, and making a tangible impact in the real world. In this role, you will design and implement systems that convert customer-captured imagery into highly accurate 3D models, enhancing the scalability and accuracy of Hover’s modeling pipeline. You will work closely with designers and engineers across various domains including frontend, backend, computer vision, and DevOps to introduce new capabilities, blending technical expertise with effective communication and cross-functional collaboration.The 3D Modeling Pipeline team creates the essential tools that our internal operations rely on to convert customer-captured scans into precise, detailed 3D models of buildings. The team also develops the pipeline and systems that process 3D data through both automated and manual steps, and export data into formats for our customers.

Hover is revolutionizing property design and protection through innovative technology. Our proprietary AI, built on over a decade of real property data, empowers users to visualize and estimate property transformations effortlessly. Homeowners, contractors, and insurance professionals depend on Hover for accurate, fully measured interactive 3D models—achieved in minutes with just a smartphone scan.At Hover, we are fueled by curiosity and purpose, committed to serving our customers, communities, and each other. We believe that diverse perspectives foster the best ideas, and we are dedicated to nurturing an inclusive, high-performance culture that promotes growth, accountability, and excellence. Supported by top investors like Google Ventures and Menlo Ventures, and trusted by industry leaders including Travelers, State Farm, and Nationwide, we are reshaping how people engage with their environments.Why We Want YouAt Hover, 3D data is at the heart of everything we do—from enhancing home visualization to transforming the construction and insurance sectors. We are seeking a Senior Software Engineer with extensive experience in 3D geometry, graphics, and visualization to help us expand the frontiers of immersive, impactful user experiences.As a key member of our 3D & Measurements team, you will play a pivotal role in developing and enhancing the core systems that power our leading products, including our PDF measurements report, Workspace for exteriors, and Virtual Walkthrough for interiors. You will collaborate closely with talented designers and engineers across frontend, backend, graphics, and DevOps to create state-of-the-art 3D solutions that meet our customers' needs.This is an exceptional opportunity to join a world-class team at the intersection of technology, design, and practical application—where your contributions will be recognized and valued daily.

ABOUT BASETENAt Baseten, we are at the forefront of enabling transformative AI solutions for some of the world's leading companies, including Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. Our innovative platform combines cutting-edge AI research, adaptable infrastructure, and developer-friendly tools to facilitate the production of advanced models. Recently, we celebrated our rapid growth with a successful $300M Series E funding round from notable investors like BOND, IVP, Spark Capital, Greylock, and Conviction. We invite you to join our dynamic team and contribute to the evolution of AI product deployment.THE ROLEAs a Senior Software Engineer specializing in Model Training at Baseten, you will play a pivotal role in constructing the infrastructure essential for the large-scale training and fine-tuning of foundational AI models. Your responsibilities will include designing and implementing distributed training systems, optimizing GPU utilization, and establishing scalable pipelines that empower Baseten and our clientele to adapt models with efficiency and reliability. This role demands a high level of technical expertise and hands-on involvement: you will be responsible for critical components of our training stack, collaborate with product and infrastructure teams to identify customer needs, and drive advancements in scalable training infrastructure.EXAMPLE WORK:Training open-source models that surpass GPT-5 capabilities for a leading digital insurerExploring specialized, continuously learning models as the future of AIOverview of our training documentationResearch initiatives we've undertakenRESPONSIBILITIESDesign, construct, and sustain distributed training infrastructures for large foundation modelsDevelop scalable pipelines for fine-tuning and training across diverse GPU/accelerator clustersEnhance training performance through optimization of algorithms and infrastructureCollaborate closely with cross-functional teams to align technical solutions with business objectivesStay abreast of advancements in the field of machine learning and AI to continually improve our training processes

At Databricks, we are dedicated to empowering data teams to tackle some of the most challenging issues of our time—from realizing the future of transportation to speeding up medical innovations. We achieve this by developing and maintaining the premier data and AI infrastructure platform, allowing our clients to leverage profound data insights to enhance their operations. Our Model Serving product equips organizations with a cohesive, scalable, and governed platform for deploying and overseeing AI/ML models, spanning traditional ML to specialized large language models. It provides real-time, low-latency inference, governance, monitoring, and lineage capabilities. With the rapid rise of AI adoption, Model Serving stands as a fundamental component of the Databricks platform, enabling clients to operationalize models efficiently and cost-effectively at scale. As a Senior Engineer, your role will be pivotal in transforming both the product experience and the underlying infrastructure of Model Serving. You will design and create systems enabling high-throughput, low-latency inference across CPU and GPU workloads, influence architectural strategies, and work closely with platform, product, infrastructure, and research teams to deliver an exceptional serving platform.

As a Senior Staff Software Engineer specializing in Model LifeCycle at Crusoe, you will play a vital role in shaping the future of software solutions that optimize and enhance our innovative operations. You will lead complex projects, mentor junior engineers, and collaborate with cross-functional teams to deliver high-impact results.

ABOUT BASETENAt Baseten, we are at the forefront of AI innovation, providing critical inference solutions for leading AI companies like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. Our platform combines advanced AI research, adaptable infrastructure, and intuitive developer tools, empowering organizations to deploy state-of-the-art models effectively. With rapid growth and a recent $300M Series E funding round backed by top-tier investors including BOND, IVP, Spark Capital, Greylock, and Conviction, we invite you to join our mission in building the platform of choice for engineers delivering AI products.THE ROLE:As a member of Baseten’s Model Performance (MP) team, you will play a pivotal role in ensuring our platform’s model APIs are not only fast and reliable but also cost-effective. Your primary focus will be on developing and optimizing the infrastructure that supports our hosted API endpoints for cutting-edge open-source models. This role involves working with distributed systems, model serving, and enhancing the developer experience. You will collaborate with a small, dynamic team at the intersection of product development, model performance, and infrastructure, defining how developers interact with AI models on a large scale.RESPONSIBILITIES:Design, develop, and maintain the Model APIs surface, focusing on advanced inference features such as structured outputs (JSON mode, grammar-constrained generation), tool/function calling, and multi-modal serving.Profile and optimize TensorRT-LLM kernels, analyze CUDA kernel performance, create custom CUDA operators, and enhance memory allocation patterns for maximum efficiency across multi-GPU setups.Implement performance improvements across various runtimes based on a deep understanding of their internals, including speculative decoding, guided generation for structured outputs, and custom scheduling algorithms for high-performance serving.Develop robust benchmarking frameworks to evaluate real-world performance across diverse model architectures, batch sizes, sequence lengths, and hardware configurations.Enhance performance across runtimes (e.g., TensorRT, TensorRT-LLM) through techniques such as speculative decoding, quantization, batching, and KV-cache reuse.Integrate deep observability mechanisms (metrics, traces, logs) and establish repeatable benchmarks to assess speed, reliability, and quality.

About Our TeamJoin the Inference team at OpenAI, where we leverage cutting-edge research and technology to deliver exceptional AI products to consumers, enterprises, and developers. Our mission is to empower users to harness the full potential of our advanced AI models, enabling unprecedented capabilities. We prioritize efficient and high-performance model inference while accelerating research advancements.About the RoleWe are seeking a passionate Software Engineer to optimize some of the world's largest and most sophisticated AI models for deployment in high-volume, low-latency, and highly available production and research environments.Key ResponsibilitiesCollaborate with machine learning researchers, engineers, and product managers to transition our latest technologies into production.Work closely with researchers to enable advanced research initiatives through innovative engineering solutions.Implement new techniques, tools, and architectures that enhance the performance, latency, throughput, and effectiveness of our model inference stack.Develop tools to identify bottlenecks and instability sources, designing and implementing solutions for priority issues.Optimize our code and Azure VM fleet to maximize every FLOP and GB of GPU RAM available.You Will Excel in This Role If You:Possess a solid understanding of modern machine learning architectures and an intuitive grasp of performance optimization strategies, especially for inference.Take ownership of problems end-to-end, demonstrating a willingness to acquire any necessary knowledge to achieve results.Bring at least 5 years of professional software engineering experience.Have or can quickly develop expertise in PyTorch, NVidia GPUs, and relevant optimization software stacks (such as NCCL, CUDA), along with HPC technologies like InfiniBand, MPI, and NVLink.Have experience in architecting, building, monitoring, and debugging production distributed systems, with bonus points for working on performance-critical systems.Have successfully rebuilt or significantly refactored production systems multiple times to accommodate rapid scaling.Are self-driven, enjoying the challenge of identifying and addressing the most critical problems.

At Crusoe, we are on a mission to accelerate the convergence of energy and intelligence. We are building a powerful engine that enables individuals to innovate boldly with AI, all while upholding principles of scalability, speed, and sustainability.Join us in spearheading the AI revolution through sustainable technology. At Crusoe, you will be at the forefront of meaningful innovation, making a significant impact while collaborating with a team dedicated to shaping the future of responsible, transformative cloud infrastructure.About the Role:As a Senior Software Engineer on the Model Lifecycle team, you will play a pivotal role in developing a managed platform that supports the entire application development lifecycle, with an emphasis on harnessing the power of Machine Learning models, particularly Large Language Models (LLMs).Your Responsibilities:Design and maintain systems for fine-tuning large foundational models (SFT, PEFT, LoRA, adapters), ensuring multi-node orchestration, checkpointing, failure recovery, and cost-effective scaling.Create and manage end-to-end training pipelines for Large Language Models.Implement components for distillation and reinforcement learning pipelines, focusing on preference optimization, policy optimization, and reward modeling.Develop and sustain the core agent execution infrastructure.Implement features for dataset, model, and experiment management, emphasizing versioning, lineage, evaluation, and reproducible fine-tuning.Collaboration and Impact:Collaborate closely with Senior Engineers, Principal Engineers, and various product and platform teams to implement systems abstractions and APIs.Engage in technical discussions surrounding training runtimes, scheduling, storage, and overall model lifecycle management.Bring 4-5+ years of industry experience, demonstrating a strong track record of successfully leading a diverse portfolio of initiatives.Participate in and contribute to the open-source LLM ecosystem.This position involves taking significant ownership of core system components.Your Qualifications:Engineering Fundamentals:Bachelor's degree in Computer Science, Engineering, or a related discipline.Proven experience in software engineering with a focus on AI models and machine learning.

OpenAI is seeking a Software Engineer in San Francisco to focus on improving productivity by optimizing model performance. This position centers on developing solutions that make machine learning models more efficient and effective. Role overview This role involves working closely with teams across different functions to identify and address areas where model performance can be improved. The aim is to deliver changes that have a measurable impact on both systems and workflows. What you will do Collaborate with engineers and other specialists to enhance model efficiency Develop and implement solutions that improve the effectiveness of machine learning systems Contribute to projects that streamline processes and drive productivity gains Impact Your work will help shape improvements in how models operate and how teams at OpenAI achieve their goals. The changes you help deliver will support more effective use of resources and better outcomes for the organization.

Waymo is a pioneering company in autonomous driving technology, dedicated to becoming the world’s most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has established the Waymo Driver—The World’s Most Experienced Driver™—with a mission to enhance mobility access and save lives lost in traffic accidents. The Waymo Driver powers our fully autonomous ride-hailing service and can be integrated across various vehicle platforms and applications. Having completed over ten million rider-only trips, our technology has driven more than 100 million miles on public roads and tens of billions in simulations across over 15 U.S. states.The Perception team is responsible for developing systems that learn the spatial-temporal representations and semantic meanings of the environment surrounding our autonomous vehicles (AVs). We collaborate closely with downstream teams to optimize and integrate our work into the Waymo Driver, conduct research to solve real-world challenges, and work alongside research teams at Alphabet. With access to millions of miles of diverse driving data from various sensors, we empower engineers like you to (1) create methods for efficient continuous learning from extensive real-world data, (2) develop scalable models and training methodologies, (3) analyze real-world behaviors to create systems that can navigate complexities, and (4) optimize models for both onboard and offboard hardware.In this hybrid role, you will report to a Technical Lead Manager.

At Databricks, we are dedicated to empowering data teams to tackle the most challenging problems in the world — from realizing the future of transportation to fast-tracking medical innovations. We accomplish this by developing and operating the premier data and AI infrastructure platform, enabling our customers to harness profound data insights for business enhancement. Our Model Serving product equips organizations with a cohesive, scalable, and governed solution for deploying and managing AI/ML models — ranging from traditional machine learning to intricate proprietary large language models. It ensures real-time, low-latency inference, governance, monitoring, and lineage. As the adoption of AI surges, Model Serving stands as a fundamental component of the Databricks platform, allowing customers to operationalize models at scale with robust SLAs and cost efficiency. In the role of Staff Engineer, you will significantly influence both the product experience and the core infrastructure of Model Serving. Your responsibilities will include designing and constructing systems that facilitate high-throughput, low-latency inference across CPU and GPU workloads, steering architectural strategies, and collaborating extensively with platform, product, infrastructure, and research teams to create an exceptional serving platform.

At Hover, we empower individuals to conceptualize, enhance, and safeguard the spaces they cherish. Utilizing proprietary AI and over a decade's worth of real property data, we provide answers to pivotal questions such as, 'What will it look like?' and 'What will it cost?' Our platform offers homeowners, contractors, and insurance professionals accurately measured, interactive 3D models of properties — all achievable from a smartphone scan in mere minutes.Driven by curiosity and purpose, we maintain a strong commitment to our customers, communities, and one another. We believe that diverse perspectives foster the best ideas, and we take pride in nurturing an inclusive, high-performance culture that encourages growth, accountability, and excellence. Supported by premier investors like Google Ventures and Menlo Ventures, and trusted by industry leaders such as Travelers, State Farm, and Nationwide, we are revolutionizing how individuals perceive and interact with their environments.About the RoleAs a Senior Software Engineer specializing in Infrastructure, you will delve into cloud infrastructure challenges unique to a company focused on 3D data, computer vision, and machine learning. Your enthusiasm for building internal tools and your talent for crafting elegant solutions to complex issues will be crucial in this role.Our Infrastructure team is responsible for everything beyond the application binary, serving as a critical partner to the rest of the engineering department. Through automation, we aim to streamline processes, ensuring that the simplest path is also the fastest and most secure. We manage and optimize all cloud infrastructure components including our Kubernetes environment, databases, networks, storage, and caching systems. Collaborating with engineering peers, we establish consistent solutions to common architectural challenges, particularly those involving rich geospatial and machine learning workloads. We are well-versed in best practices for cloud architecture and CI/CD, leveraging application development as a means to implement these practices.Your ContributionsYou will play a pivotal role in developing straightforward solutions to intriguing problems, thereby enhancing the foundation upon which our engineering teams build. Collaborating closely with engineers across the organization, you will help make their applications faster, easier to manage, and more reliable in production. Your work will span frontend, backend, computer vision, data, security, and machine learning teams to scale new ideas into production effectively. Given the small and highly collaborative nature of our team, you can expect a varied and impactful workload, which may include:Designing scalable cloud architectureEnhancing CI/CD pipelines and developer tooling

Preference Model develops reinforcement learning environments that mirror the complexity of real-world tasks. The company focuses on building diverse RL tasks and detailed reward structures, aiming to push the boundaries of artificial intelligence. The founding team brings experience from developing data infrastructure and datasets for Claude at Anthropic, and Preference Model works closely with top AI research labs. Role overview The Senior Software Engineer - Reinforcement Learning Environments position centers on designing and delivering RL environments that challenge and improve current AI models. This role involves leading complex projects, including multi-step workflows and realistic stakeholder interactions, within a large codebase. Engineers work directly with the founders and a small, collaborative team, delivering environments used for training advanced models at partner labs. The position provides significant autonomy, regular feedback, and support for professional development. What you will do Design, build, and iterate on reinforcement learning tasks, taking them from concept through evaluation. Lead the development of sophisticated environments, focusing on complex workflows and coding standards. Interact with coding agents, review their outputs, and identify subtle failures. Analyze whether issues stem from model limitations or environment design, then redesign tasks to reveal deeper failure modes. Contribute to building and maintaining the core infrastructure and tools for the environments team. Mentor junior engineers as the team expands. Location This role is based in San Francisco.

At Databricks, we are driven by our commitment to empower data teams in tackling the world's most challenging problems — from transforming transportation solutions to accelerating medical advancements. Our mission revolves around constructing and maintaining the world's premier data and AI infrastructure platform, enabling our clients to harness deep data insights for enhanced business outcomes.Foundation Model Serving represents the API product designed for hosting and serving advanced AI model inference, catering to both open-source models like Llama, Qwen, and GPT OSS, as well as proprietary models such as Claude and OpenAI GPT. We welcome engineers who have experience managing high-scale operational systems, including customer-facing APIs, Edge Gateways, or ML Inference services, even if they do not have a background in ML or AI. A passion for developing LLM APIs and runtimes at scale is essential.As a Staff Engineer, you will play a pivotal role in defining both the product experience and the underlying infrastructure. You will be tasked with designing and building systems that facilitate high-throughput, low-latency inference on GPU workloads with cutting-edge models. Your influence will extend to architectural direction, working closely with platform, product, infrastructure, and research teams to deliver an exceptional foundation model API product.The impact you will have:Design and implement core systems and APIs that drive Databricks Foundation Model Serving, ensuring scalability, reliability, and operational excellence.Collaborate with product and engineering leaders to outline the technical roadmap and long-term architecture for workload serving.Make architectural decisions to enhance performance, throughput, autoscaling, and operational efficiency for GPU serving workloads.Contribute directly to critical components within the serving infrastructure, from systems like vLLM and SGLang to developing token-based rate limiters and optimizers, ensuring seamless and efficient operations at scale.Work cross-functionally with product, platform, and research teams to transform customer requirements into dependable and high-performing systems.Establish best practices for code quality, testing, and operational readiness while mentoring fellow engineers through design reviews and technical support.Represent the team in inter-departmental technical discussions, influencing Databricks’ wider AI platform strategy.

Benchling creates software tools for scientists and biotech companies, supporting research and development across the globe. The platform serves more than 200,000 scientists, including teams at organizations like Sanofi and Moderna, as well as academic research labs. By connecting experiments, structured data, and AI-powered insights, Benchling works to reduce the time it takes for discoveries to reach real-world applications. Role overview This Software Engineer position focuses on integrating advanced scientific AI models into the Benchling platform. The main responsibility is to build a scalable system for hosting and managing scientific models, while also developing frameworks that allow model creators to bring their solutions into the Benchling environment. What you will do Develop and maintain a platform that supports scientific AI models at scale. Create frameworks that make it easier for model developers to contribute to Benchling. Experiment with new technologies to improve model integration and performance. Work closely with internal teams and external partners to deliver solutions. Help shape how scientists design molecules and apply AI in their research workflows. Location This role is based in San Francisco, CA.

Join KPFF Consulting Engineers as a Civil CAD Designer specializing in Modeling and Drafting using Civil 3D. In this dynamic role, you will contribute to innovative civil engineering projects, collaborating with a talented team to create detailed designs and plans. Your technical expertise in Civil 3D will play a crucial role in delivering high-quality results for our clients.

About World Labs: At World Labs, we create foundational world models capable of perceiving, generating, reasoning, and interacting with the 3D environment. Our mission is to unlock the full potential of AI through spatial intelligence, transforming perception into action, reasoning into insight, and imagination into creation. We believe that spatial intelligence will revolutionize storytelling, creativity, design, simulation, and immersive experiences across both virtual and physical realms. Our world-class team is driven by curiosity and passion, boasting diverse backgrounds in technology, from AI research and systems engineering to product design. This synergy fosters a tight feedback loop between our cutting-edge research and user-empowering products. Role Overview We are seeking an innovative Research Scientist specializing in generative modeling, especially diffusion models, to join our modeling team. This position is ideal for individuals with extensive expertise in applying diffusion models to images, videos, or 3D assets and scenes. While not mandatory, experience in any of the following areas will be considered a significant advantage: Large-scale model trainingResearch in 3D computer vision In this role, you will work closely with researchers, engineers, and product teams to translate advanced 3D modeling and machine learning techniques into practical applications, ensuring our technology stays at the forefront of visual innovation. This position entails substantial hands-on research and engineering work, taking projects from conception to production deployment. Key Responsibilities Design, implement, and train large-scale diffusion models for generating 3D worlds. Develop and experiment with large-scale diffusion models to introduce novel control signals, align with target aesthetic preferences, or optimize for efficient inference. Collaborate closely with research and product teams to comprehend and translate product requirements into actionable technical roadmaps. Contribute actively to all phases of model development, including data curation, experimentation, evaluation, and deployment. Continuously investigate and integrate the latest research in diffusion and generative AI. Serve as a key technical resource within the team, mentoring peers and promoting best practices in generative modeling and machine learning engineering.

At Databricks, we are dedicated to empowering data teams to tackle the most challenging global issues—whether it's transforming transportation or speeding up medical advancements. We achieve this by constructing and managing the world's leading data and AI infrastructure platform, enabling our clients to leverage deep data insights for business enhancement. The Model Serving product at Databricks offers enterprises a cohesive, scalable, and governed platform for deploying and managing AI/ML models—from conventional ML to sophisticated, proprietary large language models. It facilitates real-time, low-latency inference while providing governance, monitoring, and lineage capabilities. As AI adoption surges, Model Serving becomes a central component of the Databricks platform, allowing customers to operationalize models efficiently and cost-effectively. As a Senior Engineering Manager, you will lead a team responsible for both the product experience and the underlying infrastructure of Model Serving. This role involves shaping user-facing features while architecting for scalability, extensibility, and performance across CPU and GPU inference. You will collaborate closely with various teams across the platform, product, infrastructure, and research domains.

Role overview Meter Inc. is developing tools to capture and preserve the expertise of network engineers. The team’s goal is to build systems that document how experts diagnose network issues, making it possible for future models to manage networks with less manual effort. This work will help Meter support many customer networks while reducing the need for direct engineer intervention. What makes this work unique Network engineering lacks the structured archives found in software development. While Git and GitHub record software decisions, the reasoning behind network troubleshooting often disappears once a problem is fixed. This role centers on building a structured, searchable system for network operations, a kind of GitHub for network engineering. The system will capture network state, expert observations, and the logic behind key decisions. Your first 90 days First 30 days: Meet with network engineers to learn their workflows. Study what effective diagnostic documentation looks like and identify the necessary data. Review telemetry (ClickHouse), configurations (Postgres), and support history (Salesforce). By 60 days: Deliver a working annotation interface. Network engineers should be able to review past support tickets, view the network’s state during incidents, and record their reasoning. The tool should be practical and encourage regular use. By 90 days: Network engineers will be able to create training data independently. Initial model benchmarks from your pipeline will be live, showing how your work improves the process. Technical stack TypeScript React Go GraphQL Kafka Postgres Collaboration This role works closely with Meter’s co-founder and CEO, who will help guide the product roadmap and set priorities. Location This position is based in San Francisco.